Applied Linear Optimal Control Hardback with CD-ROM
While many books cover the theory of optimal design, few help readers to actually apply it. This book is one of the first to aid readers in utilizing the theory of optimal control to solve practical problems in the face of uncertainty. Topics covered include random inputs and random errors in measurement, uncertainty in inputs from the environment, and uncertainty in the parameters of the dynamic model. The book also addresses static and dynamic estimation, random processes, several types of controllers, smoothers, and filters. With hundreds of problems and worked examples, together with a CD-ROM containing MATLAB codes of the OPTEST, this is a comprehensive text on dynamic control, providing an excellent theoretical and practical tool for graduate students and researchers in all engineering disciplines, as well as in applied mathematics and computer science.
- Hundreds of problems and solved examples
- Includes a CD-ROM with MATLAB code, as well as code for the examples, figures, and many of the problems in the text
- Author is highly regarded and has previously published two books on this subject
Reviews & endorsements
'The author stated the goal at the beginning of the book as 'to aid readers in utilizing the theory of optimal control to solve practical problems in the face of uncertainty.' It appears this goal has been achieved. Applied Linear Optimal Control: Examples and Algorithms should be a good addition to the optimal control community. It makes an excellent text for engineering and applied mathematics students who already have some optimal control background. It is strongly recommended as a helpful guide for anyone who desires to learn and apply many of the current state of the art results in optimal control.' Applied Mechanics Reviews
Product details
August 2002Mixed media product
9780521012317
384 pages
249 × 176 × 26 mm
0.772kg
291 b/w illus. 3 tables
Unavailable - out of print
Table of Contents
- Preface
- 1. Static estimation
- 2. Random processes
- 3. Dynamic estimation - filters
- 4. Dynamic estimation - smoothers
- 5. LQ SFB follower-controllors
- 6. LQG follower-controllers
- 7. Smoothers for controlled plants
- 8. Time-invariant filters
- 9. Time-invariant LQ SFB follower-controllers
- 10. Time-invariant LQG follower-controllers
- 11. Worst case controllers
- 12. Robust TI LQG controllers
- Appendices
- References
- Index.